About CloudCV

CloudCV began in the summer of 2013 as a research project within the Machine Learning and Perception lab at Virginia Tech (now at Georgia Tech), with the ambitious goal of making platforms to make AI research more reproducible. We’re a young community working towards enabling developers, researchers, and fellow students to build, compare and share state-of-the-art Artificial Intelligence algorithms. We believe that one shouldn’t have to be an AI expert to have access to cutting edge vision algorithms. Likewise, researchers shouldn’t have to worry about building a service around their deep learning models to showcase and share it with others.

We have participated in the past five installments of Google Summer of Code, over the course of which our students built several excellent tools and features. If you are interested in participating as a student or mentor, scroll down to check out our projects and get involved! We are more than happy to answer any questions you may have regarding CloudCV, so feel free to reach out to us on our Gitter channel or on our mailing list.

Enhancements in Code Upload Pipeline

Docker Kubernetes AWS Django DRF

As EvalAI hosts more code-upload challenges and researchers utilizes our modular kubernetes based infrastructure for hosting these challenges, we would like to automate this pipeline as much as possible to enhance user experience. During GSoC 2019, we built this pipeline for evaluating AI model’s code by running it against unseen test environments in real time and this year the plan is to add features like start, stop, restart, delete cluster, etc. so as to give challenge hosts more control over their challenge evaluation cluster. This will not only involve control over the nodes running evaluation but also viewing logs which are being updated in real-time. Finally, the plan is to give challenge hosts the capability to run the evaluation cluster in their cloud by simply plugging in their keys and rest all will be taken care by EvalAI.

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Analytics Dashboard for EvalAI Users

Angular 7 Django Django Rest Framework D3.js

As the number of compute-intensive challenges on EvalAI are increasing, we want to focus on improving the performance of our services. As a first step, we will focus on monitoring and measuring all key metrics of our services. Insights from these will allow us to efficiently utilize our infrastructure, improve uptime and reduce costs. The project will concentrate on writing REST API’s, plotting pretty graphs and building analytics dashboards to cater for all three types of users on EvalAI i.e. admin, challenge hosts and participants. The analytics will help challenge hosts to view the progress of participants in their challenge for instance, comparing the trends of the accuracy from participant submissions over the period of time, etc. The final goal is to provide users with several analytics so as to display their progress on the platform and utilize the resources efficiently to reduce costs.

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Streamlining Challenge Creation on EvalAI

Python Django Django Rest Framework CI/CD tool

EvalAI is a platform to host and participate in AI challenges around the globe. To host a challenge, challenge creation is one of the core features which is utilized by challenge hosts to create AI challenges. The idea is to use private GitHub repositories to host the challenge files instead of the zip file. The next step is to build and integrate a continuous deployment pipeline with GitHub so that for every new commit in the challenge repository, the changes are automatically reflected on the UI. We will also build support for tests so that new commits are fully tested before they are pushed to the live challenge hosted on EvalAI. The goal is to enhance the challenge creation experience for challenge hosts and set up a challenge on EvalAI by the challenge hosts involving minimal human effort from the EvalAI team.

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Improvement in EvalAI Frontend

Angular 7 HTML CSS Typescript

As a part of last year’s GSOC, we took the first step towards modernizing our UI which involved shifting the current codebase from Angular 1 to Angular 7. As we’ve reached the feature parity with the existing UI, this project will involve fixing the last remaining kinks in the UI and incorporating latest UI feedback which we have received from the challenge hosts and participants for the AI challenges organized this year. The goal of this project would be to successfully replace the existing UI with the new UI after GSOC.

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Become a Mentor!

Mentoring is very important to the future of CloudCV. It introduces new people to the world of open source software who will enrich our community with their ideas and talents.

Apart from technical skills, being a mentor requires your time, a clear roadmap for your project and good organization skills. If you think you would be a good fit to mentor one of our projects, do reach out to us!

Fill this form if you have relevant experience & want to mentor.

Okay, let's mentor!

Have your own idea? Add an issue to our GSoC-Ideas repository.

In case of queries, you can contact us.

Email: team@cloudcv.org